Weavercherry1694

Allostery is among the most basic biological principles employed by biological macromolecules to achieve a biologically active state in response to chemical cues. Although initially used to describe the impact of small molecules on the conformation and activity of protein enzymes, the definition of this term has been significantly broadened to describe long-range conformational change of macromolecules in response to small or large effectors. Such a broad definition could be applied to RNA molecules, which do not typically serve as protein-free cellular enzymes but fold and form macromolecular assemblies with the help of various ligand molecules, including ions and proteins. Ligand-induced allosteric changes in RNA molecules are often accompanied by cooperative interactions between RNA and its ligand, thus streamlining the folding and assembly pathways. This chapter provides an overview of the interplay between cooperativity and allostery in RNA systems and outlines methods to study these two biological principles.Allosteric drugs are ligands that when bound to an allosteric site modify the conformational state of the pharmacological target, leading then to a modification of functional response upon binding of the endogenous ligand. Pharmacological targets are defined as biological entities, to which a ligand/drug binds and leads to a functional effect. Pharmacological targets can be proteins or nucleic acids. Computational approaches such as molecular dynamics (MD) sped up discovery and identification of allosteric binding sites and allosteric ligands. Classical all-atom and hybrid classical/quantum MD simulations can be generalized as simulation techniques aimed at analysis of atoms and molecular motion. Main limitations of MD simulations are related to high computational costs, that in turn limit the conformational sampling of biological systems. Indeed, other techniques have been developed to overcome limitations of MD, such as enhanced sampling MD simulations. In this chapter, classical MD and enhanced sampling MD simulations will be described, along with their application to drug discovery, with a focus on allosteric drugs.The p53 tumor suppressor is a multifaceted context-dependent protein, which is involved in multiple cellular pathways, with the ability to either keep the cells alive or to kill them through mechanisms such as apoptosis. To complicate this picture, cancer cells that express mutant p53 becomes addicted to the mutant activity, so that the mutant variant features a myriad of gain-of-function activities, opening different venues for therapy. This makes essential to think outside the box and apply new approaches to the study of p53 structure-(mis)function relationship to find new critical components of its pathway or to understand how known parts are interconnected, compete, or cooperate. In this context, I will here illustrate how to integrate different computational methods to the identification of possible allosteric effects transmitted from the DNA binding interface of p53 to regions for cofactor recruitment. The protocol can be extended to any other cases of study. Indeed, it does not necessarily apply only to the study of DNA-induced effects, but more broadly to the investigation of long-range effects induced by a biological partner that binds to a biomolecule of interest.Protein motions play a fundamental role in enzyme catalysis and ligand binding. The relationship between protein motion and function has been extensively investigated in the model enzyme dihydrofolate reductase (DHFR). DHFR is an essential enzyme that catalyzes the reduction of dihydrofolate to tetrahydrofolate. Numerous experimental and computational methods have been used to probe the motions of DHFR through the catalytic cycle and to investigate the effect of distal mutations on DHFR motions and ligand binding. These experimental investigations have pushed forward the study of protein motions and their role in protein-ligand interactions. QX77 price The introduction of mutations distal to the active site has been shown to have profound effects on ligand binding, hydride transfer rates and catalytic efficacy and these changes are captured by enzyme kinetics measurements. Distal mutations have been shown to exert their effects through a network of correlated amino acids and these effects have been investigated by NMR, protein dynamics, and analysis of coupled amino acids. The experimental methods and the findings that are reviewed here have broad implications for our understanding of enzyme mechanisms, ligand binding and for the future design and discovery of enzyme inhibitors.We studied the molecular details of the recognition of antigens by the variable domain of their cognate antibodies in as well as those elicited by the constant domains, which do not directly interact with antigens. Such effects are difficult to study experimentally; however, molecular dynamics simulations and subsequent residue interaction network analysis provide insight into the allosteric communication between the antigen-binding CDR region and the constant domain. We performed MD simulations of the complex of Fab and prion-associated peptide in the apo and bound forms and follow the conformational changes in the antibody and cross-talk between its subunits and with antigens. These protocols could be generally applied for studies of other antigens-antibody recognition systems.PyInteraph is a software package designed for the analysis of structural communication from conformational ensembles, such as those derived from in silico simulations, under the formalism of protein structure networks. We demonstrate its usage for the calculation and analysis of intramolecular interaction networks derived from three different types of interactions, as well as with a more general protocol based on distances between centers of mass. We use the xPyder PyMOL plug-in to visualize such networks on the three-dimensional structure of the protein. We showcase our protocol on a molecular dynamics trajectory of the Cyclophilin A wild-type enzyme, a well-studied protein in which different allosteric mechanisms have been investigated.